Sensorimotor processing during spatial navigation requires the communication between a large number of brain areas. The posterior parietal cortex (PPC) is a crucial interface for arranging this communication. Leading models, based on extensive work in primates and more recently in rodents, hypothesize that the PPC links sensory and cognitive signals, such as those that guide navigation, with the decisions and plans that drive upcoming locomotor actions. The PPC is therefore predicted to receive sensory signals as inputs and to transmit signals regarding navigation decisions and plans. Although all models of PPC function rely on the interaction between the PPC and multiple other regions, it is currently poorly understood what input signals the PPC receives and how the PPC routes output information to target regions, in large part due to technical limitations. Here we will develop and implement new approaches to measure directly the signals contained in the PPC's input and output channels. Our approach will be to use optical imaging and anatomical tracing technologies in the mouse in combination with behavioral tasks in virtual reality environments. In a first aim, we will examine how the PPC routes information related to sensory and motor events during navigation decision tasks. We will test if the PPC selectively routes different types of information to different target regions or if the PPC transmits information generally to establish widely distributed network. In a second aim, we will measure the input signals the PPC receives from the auditory cortex. We will test if these signals selectively encode specific features of the sensory world, such as spatial information, and how the input signals to the PPC are modulated depending on behavioral relevance and behavioral state. Together this work will advance our understanding of information transfer in a multi-region network for sensorimotor processing, which is essential for nearly all complex behavioral tasks.